An application of simulated annealing to optimal transcranial direct current stimulation of the human brain Article Swipe
Raheleh Tavakoli
,
Hamed Sadjedi
,
Seyyed Mohammad POURMIR FIROOZABADI
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.3906/elk-1305-134
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.3906/elk-1305-134
Transcranial direct current stimulation (tDCS) is known as the most effective technique for stimulating deeper brain areas. The capability of tDCS, however, strongly depends on the number of electrodes, their positions, and the amount of injected currents. This paper intends to apply the simulated annealing algorithm for determining optimal stimulation parameters in a multiple electrode scheme. The objective of the presented approach is to maximize the current density delivered to the target area under safety constraints. In order for the skin under the electrodes to be protected against temperature rises that may be caused by the stimulation, current injections are capped by a set of safety constraints. In the studies, the propagation of current density throughout the head is estimated via a 3D finite element approach in the ANSYS software package. Finally, the proposed algorithm is applied to a standard spherical four-layer human head model. The simulation results justify the capability of the established model in providing near optimal stimulation parameters. Accordingly, the presented approach provides neurologists with an effective tool to optimally stimulate the brains of patients.
Related Topics
Concepts
Transcranial direct-current stimulation
Simulated annealing
Human head
Adaptive simulated annealing
Computer science
Finite element method
Stimulation
Electrode
Current density
Annealing (glass)
Biomedical engineering
Brain stimulation
Head (geology)
Simulation
Electronic engineering
Control theory (sociology)
Materials science
Engineering
Neuroscience
Algorithm
Physics
Artificial intelligence
Structural engineering
Quantum mechanics
Geomorphology
Composite material
Biology
Control (management)
Geology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3906/elk-1305-134
- https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=2708&context=elektrik
- OA Status
- bronze
- Cited By
- 2
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2314920935
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2314920935Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3906/elk-1305-134Digital Object Identifier
- Title
-
An application of simulated annealing to optimal transcranial direct current stimulation of the human brainWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-01-01Full publication date if available
- Authors
-
Raheleh Tavakoli, Hamed Sadjedi, Seyyed Mohammad POURMIR FIROOZABADIList of authors in order
- Landing page
-
https://doi.org/10.3906/elk-1305-134Publisher landing page
- PDF URL
-
https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=2708&context=elektrikDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=2708&context=elektrikDirect OA link when available
- Concepts
-
Transcranial direct-current stimulation, Simulated annealing, Human head, Adaptive simulated annealing, Computer science, Finite element method, Stimulation, Electrode, Current density, Annealing (glass), Biomedical engineering, Brain stimulation, Head (geology), Simulation, Electronic engineering, Control theory (sociology), Materials science, Engineering, Neuroscience, Algorithm, Physics, Artificial intelligence, Structural engineering, Quantum mechanics, Geomorphology, Composite material, Biology, Control (management), GeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2016-01-01 |
| publication_year | 2016 |
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